The approaches described in this section could be pursued, but are not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Many enterprises and their computer systems utilize storage units that are provided by a virtual data center (VDC) and are accessible through the internet. In this arrangement, the enterprise is a client of the virtual data center (VDC). Storage units provided by the virtual data center may be virtualized storage pools, comprised of partitioned portions of multiple different physical storage devices at the virtual data center. Such clients also may instantiate CPU resources to perform work in a VDC in cooperation with the storage units. In such an arrangement, the utilization of storage may be managed independently of CPU resources.
Such cloud storage services may provide a client with many benefits, such as reduced storage costs, easier scalability, and a reduced administrative burden. However, a drawback of such cloud storage systems is that the performance of storage units provided by the virtual data center often varies greatly; there may be significant variation in the time needed to complete a read operation or a write operation. Furthermore, enterprise clients often pay similar amounts for different storage units that perform in a drastically different manner. Approaches for obtaining higher quality performance from cloud storage units are needed.